1,546 research outputs found
A Simple Cooperative Diversity Method Based on Network Path Selection
Cooperative diversity has been recently proposed as a way to form virtual
antenna arrays that provide dramatic gains in slow fading wireless
environments. However most of the proposed solutions require distributed
space-time coding algorithms, the careful design of which is left for future
investigation if there is more than one cooperative relay. We propose a novel
scheme, that alleviates these problems and provides diversity gains on the
order of the number of relays in the network. Our scheme first selects the best
relay from a set of M available relays and then uses this best relay for
cooperation between the source and the destination. We develop and analyze a
distributed method to select the best relay that requires no topology
information and is based on local measurements of the instantaneous channel
conditions. This method also requires no explicit communication among the
relays. The success (or failure) to select the best available path depends on
the statistics of the wireless channel, and a methodology to evaluate
performance for any kind of wireless channel statistics, is provided.
Information theoretic analysis of outage probability shows that our scheme
achieves the same diversity-multiplexing tradeoff as achieved by more complex
protocols, where coordination and distributed space-time coding for M nodes is
required, such as those proposed in [7]. The simplicity of the technique,
allows for immediate implementation in existing radio hardware and its adoption
could provide for improved flexibility, reliability and efficiency in future 4G
wireless systems.Comment: To appear, IEEE JSAC, special issue on 4
Massive MIMO for Internet of Things (IoT) Connectivity
Massive MIMO is considered to be one of the key technologies in the emerging
5G systems, but also a concept applicable to other wireless systems. Exploiting
the large number of degrees of freedom (DoFs) of massive MIMO essential for
achieving high spectral efficiency, high data rates and extreme spatial
multiplexing of densely distributed users. On the one hand, the benefits of
applying massive MIMO for broadband communication are well known and there has
been a large body of research on designing communication schemes to support
high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT)
is still a developing topic, as IoT connectivity has requirements and
constraints that are significantly different from the broadband connections. In
this paper we investigate the applicability of massive MIMO to IoT
connectivity. Specifically, we treat the two generic types of IoT connections
envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable
low-latency communication (URLLC). This paper fills this important gap by
identifying the opportunities and challenges in exploiting massive MIMO for IoT
connectivity. We provide insights into the trade-offs that emerge when massive
MIMO is applied to mMTC or URLLC and present a number of suitable communication
schemes. The discussion continues to the questions of network slicing of the
wireless resources and the use of massive MIMO to simultaneously support IoT
connections with very heterogeneous requirements. The main conclusion is that
massive MIMO can bring benefits to the scenarios with IoT connectivity, but it
requires tight integration of the physical-layer techniques with the protocol
design.Comment: Submitted for publicatio
Multi-Antenna Assisted Virtual Full-Duplex Relaying with Reliability-Aware Iterative Decoding
In this paper, a multi-antenna assisted virtual full-duplex (FD) relaying
with reliability-aware iterative decoding at destination node is proposed to
improve system spectral efficiency and reliability. This scheme enables two
half-duplex relay nodes, mimicked as FD relaying, to alternatively serve as
transmitter and receiver to relay their decoded data signals regardless the
decoding errors, meanwhile, cancel the inter-relay interference with
QR-decomposition. Then, by deploying the reliability-aware iterative
detection/decoding process, destination node can efficiently mitigate
inter-frame interference and error propagation effect at the same time.
Simulation results show that, without extra cost of time delay and signalling
overhead, our proposed scheme outperforms the conventional selective
decode-and-forward (S-DF) relaying schemes, such as cyclic redundancy check
based S-DF relaying and threshold based S-DF relaying, by up to 8 dB in terms
of bit-error-rate.Comment: 6 pages, 4 figures, conference paper has been submitte
MIMO signal processing in offset-QAM based filter bank multicarrier systems
Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft
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